Long content (e.g., text, audio, or video content) may be tedious to consume by users. Long content may be split into portions of predetermined size. For example, text may be paginated every 60 lines or an audio or video file may be segmented into five-minute portions.
A long short-term memory (LSTM) is a recurrent neural network that can learn from experience. A LSTM comprises a set of LSTM cells. Each LSTM cell provides an output based on an input and one or more internal states. Compared with other recurrent neural networks, LSTMs tend to be better at remembering values for long or short periods of time because of the specific gating mechanism used by LSTMs. As a result, stored values within the LSTM cells do not inherently degrade over time. LSTMs find application in, among other things, natural-language text compression, handwriting recognition, and automatic speech recognition.